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タイトル: | Early-warning prediction of student performance and engagement in open book assessment by reading behavior analysis |
著者: | Flanagan, Brendan ![]() ![]() ![]() Majumdar, Rwitajit ![]() ![]() Ogata, Hiroaki ![]() ![]() ![]() |
著者名の別形: | 緒方, 広明 |
キーワード: | Early warning prediction Open-book assessment Reading behavior Student modeling |
発行日: | 2022 |
出版者: | Springer Nature |
誌名: | International Journal of Educational Technology in Higher Education |
巻: | 19 |
論文番号: | 41 |
抄録: | Digitized learning materials are a core part of modern education, and analysis of the use can offer insight into the learning behavior of high and low performing students. The topic of predicting student characteristics has gained a lot of attention in recent years, with applications ranging from affect to performance and at-risk student prediction. In this paper, we examine students reading behavior using a digital textbook system while taking an open-book test from the perspective of engagement and performance to identify the strategies that are used. We create models to predict the performance and engagement of learners before the start of the assessment and extract reading behavior characteristics employed before and after the start of the assessment in a higher education setting. It was found that strategies, such as: revising and previewing are indicators of how a learner will perform in an open ebook assessment. Low performing students take advantage of the open ebook policy of the assessment and employ a strategy of searching for information during the assessment. Also compared to performance, the prediction of overall engagement has a higher accuracy, and therefore could be more appropriate for identifying intervention candidates as an early-warning intervention system. |
著作権等: | © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. |
URI: | http://hdl.handle.net/2433/279308 |
DOI(出版社版): | 10.1186/s41239-022-00348-4 |
出現コレクション: | 学術雑誌掲載論文等 |
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